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Systematic Analysis and Methodologies for Hardware Security

With the increase in globalization of Integrated Circuit (IC) design and production,
hardware trojans have become a serious threat to manufacturers as well as
consumers. These trojans could be intensionally or accidentally embedded in ICs to
make a system vulnerable to hardware attacks. The implementation of critical applications
using ICs makes the effect of trojans an even more serious problem. Moreover,
the presence of untrusted foundries and designs cannot be eliminated since the need
for ICs is growing exponentially and the use of third party software tools to design
the circuits is now common. In addition if a trusted foundry for fabrication has to
be developed, it involves a huge investment. Therefore, hardware trojan detection
techniques are essential. Very Large Scale Integration (VLSI) system designers must
now consider the security of a system against internal and external hardware attacks.
Many hardware attacks rely on system vulnerabilities. Moreover, an attacker may
rely on deprocessing and reverse engineering to study the internal structure of a system
to reveal the system functionality in order to steal secret keys or copy the system.
Thus hardware security is a major challenge for the hardware industry. Many hardware
attack mitigation techniques have been proposed to help system designers build
secure systems that can resist hardware attacks during the design stage, while others
protect the system against attacks during operation.
In this dissertation, the idea of quantifying hardware attacks, hardware trojans,
and hardware trojan detection techniques is introduced. We analyze and classify hardware
attacks into risk levels based on three dimensions Accessibility/Resources/Time
(ART). We propose a methodology and algorithms to aid the attacker/defender to
select/predict the hardware attacks that could use/threaten the system based on the
attacker/defender capabilities. Because many of these attacks depends on hardware
trojans embedded in the system, we propose a comprehensive hardware trojan classification based on hardware trojan attributes divided into eight categories. An adjacency
matrix is generated based on the internal relationship between the attributes
within a category and external relationship between attributes in different categories.
We propose a methodology to generate a trojan life-cycle based on attributes determined
by an attacker/defender to build/investigate a trojan. Trojan identification
and severity are studied to provide a systematic way to compare trojans. Trojan
detection identification and coverage is also studied to provide a systematic way to
compare detection techniques and measure their e effectiveness related to trojan severity.
We classify hardware attack mitigation techniques based on the hardware attack
risk levels. Finally, we match these techniques to the attacks the could countermeasure
to help defenders select appropriate techniques to protect their systems against
potential hardware attacks. / Graduate / 0544 / 0984 / samerm@uvic.ca

  1. http://hdl.handle.net/1828/6954
  2. Samer Moein, Fayez Gebali. "Quantifying Overt Hardware Attacks: Using ART Schema." Computer Science and its Applications. Springer Berlin Heidelberg, pp. 511-516. 2015.
  3. Samer Moein, Fayez Gebali, and T. Aaron Gulliver ." Hardware Attack Mitigation Techniques Based on Hardware Attack Risk Levels."In IEEE Access, 2015. Submitted.
  4. Samer Moein, T. Aaron Gulliver, and Fayez Gebali." Hardware Trojan Detection and Identification."In IEEE Access, 2015. Submitted.
  5. Samer Moein, Fayez Gebali, and T. Aaron Gulliver. "Hardware Attacks: An Algebraic Approach." In Journal of Cryptographic Engineering (JCEN), 2015.
  6. Samer Moein, T. Aaron Gulliver, and Fayez Gebali." A New Characterization of Hardware Trojan Attributes." In IEEE Transaction on Security and Forensics, 2015. Submitted.
  7. Samer Moein, Fayez Gebali, and Issa Traore. "Analysis of Covert Hardware Attacks." In Journal of Convergence Volume 5.3, 2014.
  8. Sabah Al-Fedaghi, and Samer Moein. "Modeling Attacks." In International Journal of Safety and Security Engineering 4.2, pp. 97-115, 2014.
  9. Nicholas Houghton, Samer Moein, and Fayez Gebali. "A Web Based Tool For Classifying Hardware Trojans."In IEEE International Symposium on Circuits and Systems (ISCAS ’16), 2016. Submitted.
  10. Samer Moein, Jayaram Subramnian, T. Aaron Gulliver, Fayez Gebali, and M. Watheq El-Kharashi. "Classification of Hardware Trojan Detection Techniques." In IEEE International Conference on Computer Engineering and Systems (ICCES ’15), 2015.
  11. Samer Moein, Salman Khan, T. Aaron Gulliver, Fayez Gebali, and M. Watheq El-Kharashi. "An Attribute Based Classification of Hardware Trojans." In IEEE International Conference on Computer Engineering and Systems (ICCES ’15), 2015.
  12. Samer Moein, Fayez Gebali, T. Aaron Gulliver, and M. Watheq El-Kharashi. "Hardware Attack Risk Assessment." In IEEE International Conference on Computer Engineering and Systems (ICCES ’15), 2015.
  13. Ali Alzahrani, Samer Moein, Nicholas Houghton, and Fayez Gebali. "CRT Based Somewhat Homomorphic Encryption Over the Integers."In IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim ’15), 2015.
  14. Samer Moein, and Fayez Gebali. "A Formal Methodology for Quantifying Overt Hardware Attacks." In Proceedings of the 9th International Conference on Computer Engineering and Applications (CEA ’15), pp. 63-69 , 2015.
  15. Samer Moein, and Fayez Gebali. "Quantifying Covert Hardware Attacks: Using ART Schema."In Proceedings of the 9th International Conference on Computer Engineering and Applications (CEA ’15), pp. 85-90, 2015.
Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/6954
Date18 December 2015
CreatorsMoein, Samer
ContributorsGebali, Fayez, Gulliver, T. Aaron
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
RightsAvailable to the World Wide Web

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